499 results about "Noise power" patented technology

The invention discloses a hybrid intelligent reflecting surface assistance-based communication and sensing integration method, and relates to the technical field of wireless communication, and the method comprises the steps: building a communication and sensing integration system which comprises a dual-function base station, a hybrid intelligent reflecting surface, K communication users and L sensing targets; the method comprises the following steps of: constructing a communication model and a perception model; establishing an optimization problem of maximizing the minimum sensing beam gain in the L sensing targets under the condition of satisfying the maximum transmission total power constraint of the dual-function base station, the communication user communication quality constraint, the maximum transmission total power constraint of the hybrid intelligent reflecting surface and the noise power constraint; and carrying out conversion solution on the optimization problem based on an alternating variable iterative optimization algorithm to obtain a final optimal solution of the optimization problem. According to the invention, the minimum sensing beam gain of the sensing target can be maximized, and the sensing capability of the system is improved.

The invention discloses a resource allocation optimization method for a multi-IRS unmanned aerial vehicle communication-sensing-calculation integrated system, and the method improves the safety rate of the system through employing a multi-IRS-assisted sensing beam and a communication beam, and reducing the signal-to-interference-noise ratio (SINR) of an eavesdropper through artificial noise. The invention provides a hybrid SAC intelligent optimization algorithm based on deep reinforcement learning. According to the algorithm, discrete actions such as deployment points, task unloading ratios, artificial noise power and the like of D-UAV and I-UAV are optimized in a combined mode through a discrete SAC algorithm, continuous actions such as IRS phase shift and the like are optimized through a continuous SAC algorithm, and the aim is to optimize the safety rate of a system. Simulation results show that the intelligent optimization scheme provided by the invention is superior to other comparison schemes under different transmitting powers and different numbers of IRS arrays.

The invention relates to a channel estimation method based on frequency domain deviation compensation and dynamic DCT denoising, and belongs to the technical field of wireless communication. The method comprises the following steps: establishing a wireless channel model and an OFDM system model; estimating the frequency offset in the received signal by using the phase rotation characteristic of the pilot signal; calculating a preliminary channel frequency domain response # imgabs2 # at a pilot frequency position through a least square criterion based on the compensation signal # imgabs1 #; obtaining a receiving pilot frequency signal # imgabs4 # according to the sending pilot frequency Xp and the roughly estimated channel frequency response # imgabs3 #; estimating a current signal-to-noise ratio SNRest based on the pilot frequency signal # imgabs5 # and a noise power ratio; and establishing an adaptive DCT denoising strategy based on a signal-to-noise ratio threshold, and selecting different denoising strategies according to different signal-to-noise ratios to perform denoising processing on # imgabs6 # to obtain final channel estimation # imgabs7 #. The adaptive denoising strategy design of the invention effectively balances the relationship between noise suppression and channel structure fidelity, and improves the precision and stability of overall channel estimation.

The invention discloses a power supply communication method and device based on power line carrier communication, and relates to the technical field of power supply communication. Problems of signal attenuation, insufficient anti-interference capability, insufficient stability of power supply communication, insufficient intelligent path switching capability and the like exist in the prior art. According to the method, high-sampling-rate PSD analysis, STFT and LSTM are adopted to predict noise power time sequence data, and a noise-load rate coupling model is established; secondly, based on a transmission line theory, researching channel time-varying characteristics, calculating signal reflection and multipath effects, and calculating channel coherence time through a sliding window; for signal attenuation, low, medium and high frequency band models are respectively established, path attenuation is calculated, and channel capacity is optimized; and finally, through real-time stability analysis, short-term and long-term SNR stability is calculated, and path selection is optimized in combination with a load rate, so that communication quality is ensured. And through integration of channel modeling, time-varying analysis and path optimization, the reliability and stability of power line carrier communication are improved.

The invention discloses a turning signal noise reduction method based on an improved wavelet threshold, and the method comprises the steps: carrying out the multi-layer wavelet decomposition of a noise-containing turning signal, obtaining the low-frequency and high-frequency wavelet coefficients of each layer, and processing the high-frequency wavelet coefficients of each layer through an improved threshold function, thereby achieving the noise reduction of the turning signal. And reconstructing a signal through wavelet inverse transformation of the processed wavelet coefficient to realize denoising. The optimal number of decomposition layers required by a sampling signal is determined according to noise power, and finally, an optimal wavelet basis is determined by taking a signal-to-noise ratio, a mean square error and the like as evaluation indexes. By means of the improved wavelet threshold function, on one hand, the signal denoising effect can be achieved, and on the other hand, the situation that details are damaged due to excessive noise reduction can be avoided. Experimental data show that the improved threshold function effectively suppresses random errors, the signal-to-noise ratio is improved, the root-mean-square error is reduced, and the denoising effect is good.

The invention discloses a sparse Bayesian direction of arrival estimation method based on subspace compression and dictionary optimization, and belongs to the field of array signal processing. According to the method, the data dimension is reduced through the subspace compression technology, and the noise immunity is improved; signal power and noise power are automatically estimated in combination with a sparse Bayesian model, and dependence on information source number information is avoided; the calculation efficiency and the numerical stability are improved through a support set adaptive pruning strategy; and finally, a dictionary fine tuning mechanism is introduced, direction continuous optimization is realized on the basis of an original discrete grid, an off-grid error is eliminated, and direction-of-arrival estimation with sub-resolution precision is realized. The method is a novel method combining subspace compression, sparse Bayesian inference, adaptive pruning and angle optimization, can give consideration to estimation precision, calculation efficiency and application robustness, and is especially suitable for direction estimation under the complex actual conditions of low signal-to-noise ratio, few snapshots, unknown signal source number and the like.

The invention relates to the technical field of satellite transmission service or radio transmission service of a space station or an airborne station, in particular to a narrow-band interference elimination method based on spread spectrum communication applied to satellite transmission service, which comprises the following steps: S1, performing FFT (Fast Fourier Transform) operation on a digital baseband signal, converting the digital baseband signal into a frequency domain signal, determining a judgment threshold according to the background noise power, and judging a component greater than the threshold as an interference signal; s2, based on a sequential return-to-zero algorithm or a sequential pruning algorithm, frequency points with interference signal components in each frequency domain under the AWGN condition are cut off; s3, using windowed FFT operation, and popularizing the application under the AWGN condition in the S2 to the application under the narrowband interference condition; and S4, reducing the frequency domain signal after the interference signal component frequency points are removed into a time domain signal by adopting IFFT (Inverse Fast Fourier Transform) operation. The method has a good application prospect in the fields of manufacturing of space-based satellite systems and other spacecrafts, manufacturing of satellite antennas and other communication system equipment, satellite transmission services and the like.

The invention discloses a differential noise traction system and a differential signal noise parameter measurement method and device, and belongs to the field of chip measurement. The system is characterized in that a vector network analyzer comprises four ports, the input ends of two impedance tuners are respectively connected to a differential output port pair of the vector network analyzer, the output ends of the two impedance tuners are respectively connected to the differential input end of a tested device, the differential output end of the tested device is connected to the receiving end of a noise receiver, and the noise receiver is connected to the output end of the noise receiver. The output end of the noise receiver is respectively connected to a differential receiving port pair of the vector network analyzer; the direct-current power supply is used for supplying power to the tested device and the switch controller, and the switch controller is used for controlling an internal switch of the noise receiver; the differential output port pair generates a differential signal; the differential receiving port pair is used for receiving noise power of a differential signal; and the impedance tuner is used for adjusting the impedance point, so that the differential signals input to the tested device correspond to different differential impedances. The method can improve the measurement precision.

The invention provides a vector array sparse Bayesian learning direction of arrival estimation method. The method comprises the following steps: constructing a far-field vector sparse signal model; and establishing a noise covariance model under the vector sound field. And estimating a signal power hyper-parameter through a vector array sparse Bayesian learning process. And through a maximum likelihood estimation technology, noise power hyper-parameter estimation is realized. And finally, carrying out peak searching on the converged signal power hyper-parameter to obtain a direction of arrival estimation result. The method has the advantages that the vector array signal processing performance advantage is obtained, higher signal processing gain is obtained, and meanwhile the method has the capability of restraining the azimuth ambiguity problem; and by using the difference between the noise covariance matrix and the signal covariance matrix under the vector noise, the estimation precision of hyper-parameters such as the signal power and the noise power is remarkably improved. Compared with a traditional vector array DOA estimation method, the vector array DOA estimation method has a lower spectrum background and a sharper spatial spectrum peak, and the resolution and DOA estimation precision are remarkably superior to those of other methods.

A method is performed by an endpoint device that includes a loudspeaker, a microphone, and a controller. The method includes: by the loudspeaker, playing a loudspeaker signal into a space; by the microphone, detecting audio in the space, to produce a feedback audio signal; estimating acoustic parameters for the space including a reverberation time and an ambient noise power based on the feedback audio signal and the loudspeaker signal; receiving an incoming audio signal that is not detected by the microphone; using the acoustic parameters, generating an acoustic watermark signal that, when played into the space through the loudspeaker, would be inaudible to a listener; adding the acoustic watermark signal to the incoming audio signal to produce a watermarked audio signal; and playing the watermarked audio signal into the space through the loudspeaker.

A method of a wireless communication device, includes compensating for a first phase of a first training symbol and a second phase of a second training symbol following the first training symbol, based on a reference carrier frequency offset (CFO) corresponding to one of a plurality of subcarriers of a received frame in a time domain; calculating residual CFOs respectively for the plurality of subcarriers of the received frame, based on the reference CFO; compensating for phase differences between the first training symbol and the second training symbol for each of the plurality of subcarriers, based on the residual CFOs in a frequency domain; and estimating at least one of noise power and signal-to-noise ratio (SNR) of the received frame, based on the first training symbol and the second training symbol after compensating for the phase differences between the first training symbol and the second training symbol.

A measurement system for determining a noise figure of a device under test is described. The measurement system determines a first total error power based on the output signal by a first noise canceling technique, wherein the first total error power includes systematic errors originating in the device under test and in the measurement system. The measurement system determines a second total error power based on the output signal by a different, second noise canceling technique. The second total error power includes systematic errors originating in the measurement system. The second total error power further includes noise originating in the device under test and in the measurement system outside of the measurement instrument. The measurement system is configured to subtract the first total error power from the second total error power, thereby obtaining an external noise power.

The invention provides a filtering method and device for channel estimation, electronic equipment and a storage medium. The method comprises the following steps: acquiring initial channel estimation of a reference signal, and determining optimal noise power in a current target channel scene based on the initial channel estimation; performing first-stage Wiener filtering on the initial channel estimation to obtain first filtering channel estimation; and performing second-stage Wiener filtering on the first filtering channel estimation based on the optimal noise power to obtain second filtering channel estimation. Therefore, according to the scheme, the optimal noise power in the target channel scene is acquired in advance, so that the second-stage Wiener filtering can be immediately carried out after the first-stage Wiener filtering is completed, the process of carrying out noise estimation on the reference signal after the first-stage filtering can be omitted, the processing waiting time is reduced, and the processing efficiency is improved. And the processing time delay is reduced, so that the two-stage filter circuit can be designed in a tight coupling manner to enhance the stability of the filter performance.

The invention discloses a cable partial discharge signal noise separation mode identification method and system, and particularly relates to the technical field of cable partial discharge detection, in a multi-cable stacking environment, partial discharge signals are synchronously collected through multiple types of sensors such as a high-frequency current sensor, an ultrasonic sensor and an electromagnetic antenna; performing band-pass filtering, wavelet denoising and multi-channel synchronous alignment on the acquired signals to suppress background noise and retain key features of partial discharge pulses; separating the mixed signals by adopting independent component analysis; calculating a decision coefficient based on an inter-channel correlation coefficient, a signal-noise power ratio and an amplitude dynamic range, and judging whether to introduce a denoising method based on deep learning; for the waveform after noise separation, executing an amplitude re-calibration process so as to correct amplitude scaling uncertainty, and extracting multi-dimensional time domain, frequency domain and phase features; and a support vector machine and other machine learning algorithms are combined to realize automatic identification of partial discharge types.

Some embodiments of the present disclosure relate to apparatuses and methods for establishing signal-to-noise ratio (SNR), available signal power level (Es), and man-made noise power level (Noc) values for new radio (NR) performance requirements. These apparatuses and methods may include processing a received signal including the Es and Noc; and determining a baseband SNR attenuation based on the signal power level, the man-made noise power level, and the radio frequency noise power level. These apparatuses and methods may then determine a compensated SNR attenuation as a performance requirement based on the baseband SNR attenuation and the radio frequency noise power level.

The invention discloses a method for adjusting transmitting power in satellite communication, and belongs to the technical field of satellite communication. The method comprises the following steps: firstly, scanning a communication frequency band and an adjacent frequency band by using spectrum monitoring equipment on a satellite, constructing a plurality of background noise power sequences and extracting background noise features; a corresponding sequence is formed according to the bit error rate and the signal-to-noise ratio of the satellite emission signal, and bit error rate features and signal-to-noise ratio features are extracted; acquiring a demand coefficient according to the newest bit error rate and the difference between the signal-to-noise ratio and the target value; and finally, inputting a plurality of groups of background noise features, bit error rate features, signal-to-noise ratio features and demand coefficients as samples into the trained full connection layer-BP neural network to obtain a transmitting power increment, adding the transmitting power increment with the initial transmitting power, and determining the transmitting power of the next signal, thereby effectively improving the transmitting power adjustment precision.

The invention discloses a multi-bandwidth spectrum data signal adaptive extraction method based on a signal-to-noise ratio threshold, and relates to the technical field of spectrum signal extraction. The frequency spectrum data collection covers 30MHz-6GHz, the sampling rate is 20MHz, 16-bit quantization is realized, and the hardware fluctuation is eliminated through the dual-channel design; according to noise floor estimation, 50 frames of no-signal samples are taken, mean value calculation is carried out through a sliding window, then median filtering is carried out, and the noise power and confidence interval of each frequency point are obtained; basic values are set for a signal-to-noise ratio threshold according to frequency bands, dynamic adjustment is performed in combination with real-time noise standard deviation, and compensation is added to a known frequency band; for multi-bandwidth detection, wavelet packet decomposition is adapted to 100kHz-5MHz, candidate signals are marked when energy detection exceeds a threshold, and a range is determined by morphological filtering; extracting parameters such as center frequency, analyzing time-frequency characteristics through short-time Fourier transform, and calculating 4-order cumulants to establish feature vectors; coherent accumulation times are adjusted according to a signal-to-noise ratio, energy is superposed through phase alignment, and a purified signal is output through band-pass filtering. According to the invention, the signal detection precision and adaptability in a complex environment are improved, and misjudgment is reduced.

The present invention provides a soft decision audio decoding system for maintaining audio continuity in a digital wireless audio receiver, which infers the likelihood of errors in a received digital signal based on generated hard bits and soft bits. The soft audio decoder can utilize the soft bits to determine whether the digital signal should be decoded or muted. The soft bits can be generated based on a detection point and detected noise power or by using a soft output Viterbi algorithm. The value of the soft bits can indicate the confidence in the strength of the hard bit generation. The soft decision audio decoding system can infer errors and decode perceptually acceptable audio without error detection as in conventional systems and has low latency and improved granularity.

A temperature control device for a non-magnetic packaging VCSEL laser comprises a main control module which adopts NI equipment and a LabVIEW program, provides high-resolution data acquisition and real-time PID parameter adjustment, and realizes accurate temperature control. And the high-frequency modulation module shifts the temperature control signal to a high frequency band to suppress low-frequency magnetic field noise. The power supply module is composed of a switching power supply and a voltage stabilizing circuit, provides a stable power supply for the power amplifier operational amplifier and the radiator, and reduces noise and transient interference. The power amplification module is composed of two stages of amplification circuits, and a low-noise amplifier and a high-frequency current feedback amplifier are adopted to achieve efficient power amplification of signals. The heating module comprises a double-layer 2N polar distance heating film and an NTC negative feedback thermistor, the upper magnetic field and the lower magnetic field of a heating coil are mutually offset, non-magnetic heating is ensured, meanwhile, the NTC thermistor is combined for accurate temperature measurement, current is controlled in cooperation with a PID algorithm, and temperature stability is ensured. Compared with the prior art, the device has remarkable advantages in the aspects of non-magnetic heating, low-noise power supply and temperature control precision.

Embodiments of the present application provide a blind detection result acquisition method and apparatus, a storage medium, and an electronic device. The method comprises: determining estimation value groups respectively corresponding to a plurality of synchronization signal blocks to be subjected to blind detection, wherein each estimation value group comprises a plurality of channel estimation values corresponding to one synchronization signal block; for each synchronization signal block among the plurality of synchronization signal blocks, on the basis of noise power and reference signal received power corresponding to the estimation value group of each synchronization signal block, determining the signal-to-noise ratio of each synchronization signal block so as to obtain the signal-to-noise ratios respectively corresponding to the plurality of synchronization signal blocks; and on the basis of the signal-to-noise ratios respectively corresponding to the plurality of synchronization signal blocks, determining the synchronization signal block having the maximum signal-to-noise ratio among the plurality of synchronization signal blocks, and determining the synchronization signal block having the maximum signal-to-noise ratio as a blind detection result. The problems in the related art of complex algorithms, high resource overhead during implementation by means of hardware, etc., in existing issb blind detection solutions are solved.

The invention discloses a high-precision magnetic field data acquisition unit for aeromagnetic measurement and an acquisition method thereof, belongs to the technical field of aeromagnetic measurement, and solves the problems that the acquisition resolution of an aeromagnetic measurement magnetic field is low, the measurement precision is influenced by a power supply and electromagnetic interference, and the data processing and storage reliability is insufficient. According to the invention, a framework of'acquisition module + control module 'is adopted, the acquisition module realizes high-precision sampling through low-noise power supply, differential reference and analog front-end full-link conditioning, the control module completes error compensation and aeromagnetic compensation through a Zynq core, and the 1nT-level magnetic field acquisition precision is achieved by matching an anti-interference design and stable storage and transmission. The 1nT-level magnetic field acquisition precision in the aeromagnetic measurement process is achieved, the signal acquisition precision and stability are remarkably improved, electromagnetic and power interference is effectively inhibited, the reliability of data processing, storage and transmission is guaranteed, and the strict requirements of aeromagnetic measurement for precision and interference resistance are met.

The invention discloses a frequency offset estimation method and device, which are applied to the field of communication, a receiving end extracts a power time delay sub-spectrum in a noise window from a first power time delay spectrum of a reference signal, determines noise power based on a first power value in the power time delay sub-spectrum, and determines a weight coefficient of the reference signal based on the noise power. The weight coefficient is negatively correlated with the noise power, and the noise power is negatively correlated with the signal-to-noise ratio of the reference signal, so that the weight coefficient is positively correlated with the signal-to-noise ratio of the reference signal, and the weight of the reference signal with the high signal-to-noise ratio is adaptively increased. According to the invention, if the first power time delay spectrum of the plurality of reference signals is determined, weighting processing is carried out on the first power time delay spectrum of the plurality of reference signals based on the weight coefficients of the plurality of reference signals to obtain the second power time delay spectrum, so that the determined second power time delay spectrum can be ensured to accord with the change of the channel, and the real-time performance is good. Therefore, the accuracy of the determined frequency offset is relatively high based on the target time domain channel response value of the first time delay index in the second power time delay spectrum.

Various embodiments of the present disclosure disclose improved BIST systems and methods for testing digital devices. A method for testing a digital device includes receiving, based at least in part on an input signal, an output signal from a device under testing (DUT). The output signal is processed to generate a noise signal and a recovered signal for the DUT. The controller may generate a signal to noise power ratio based at least in part on the noise and recovered signals and compare the signal to noise power ratio to a predetermined power threshold to generate a performance metric.

The invention discloses a subarray beam domain high-resolution spatial spectrum estimation method under an under-snapshot condition. The method comprises the following steps: step 1, uniformly dividing N-element towed linear array sonar array element frequency domain data into K subarrays; 2, performing beam forming processing on each piece of sub-array data to obtain a beam domain result of each sub-array; 3, calculating a beam domain steering vector; 4, calculating a beam domain covariance matrix; 5, realizing signal and noise power parameter estimation based on a sparse approximate minimum variance criterion; and 6, carrying out frequency band weighted summation on the estimated signal power to obtain a broadband DOA estimation result. According to the method, sub-array division dimensionality reduction, beam domain coherent processing and sparse parameter iteration estimation are combined for processing, the method has the advantages of low snapshot adaptability and high anti-interference capability, the method can be used for near-field weak signal detection of the towed linear array under multi-target interference, and effectiveness is verified through marine test data.

The embodiment of the invention provides a short-wave full-frequency staring-distributed cooperative frequency, channel and link measurement method. The method is applied to the field of short-wave measurement, and comprises the following steps: performing multi-phase filtering on a received broadband signal to obtain a multi-channel signal; determining signal power and noise power of the multi-channel signal, and determining frequency availability according to the signal power and the noise power; selecting an available frequency according to the frequency availability, measuring through a linear frequency modulation signal transmitted in a channel to obtain a channel characteristic parameter, and determining the channel availability according to the channel characteristic parameter; signals with different waveforms are transmitted in a specified link, link characteristics are obtained through measurement, and link availability is determined according to the link characteristics; the frequency availability, the channel availability and the link availability are subjected to statistical analysis to obtain a statistical analysis result, data support is provided for multi-link cooperative transmission strategy adjustment and link access decision, and the efficiency and reliability of short-wave communication are improved.

The invention provides a target orientation estimation algorithm based on covariance matrix imaginary part reconstruction for solving the problems that the underwater environment is complex and weak signals are difficult to detect. The algorithm includes calculating a covariance matrix from array received data; extracting an imaginary part of the covariance matrix, and reconstructing a new covariance matrix according to the characteristic value and the corresponding characteristic vector of the imaginary part; initializing a variable factor and a noise power estimation value; calculating initial values of a spatial orientation spectrum and sparseness thereof; on the basis of a sparse approximate minimum variance principle, iteratively calculating the spatial orientation spectrum until convergence; normalization processing is carried out on the iteration space azimuth spectrum, angles corresponding to the first K maximum values are target azimuth estimation values, and K is the real number of target signals. According to the method, the covariance matrix is reconstructed by extracting the covariance matrix imaginary part, so that the influence of noise on weak signals is weakened; and on the other hand, the estimation performance of the weak signal and the sparseness of the azimuth spectrum are considered by adaptively adjusting the variable factor, and the resolution capability of the weak target is enhanced.

The invention provides a signal detection method and device, equipment, a chip and a medium, and the method comprises the steps: obtaining a receiving signal corresponding to a control resource set CORESET to be subjected to blind detection; determining signal power and noise power of a control channel element (CCE) corresponding to the candidate physical downlink control channel (PDCCH) according to the pilot signal and the received signal of the CORESET; according to the signal power and the noise power of the CCE, determining the total signal-to-noise ratio of the candidate PDCCH and the target signal-to-noise ratio of the CCE; and determining whether the candidate PDCCH contains an effective signal according to the total signal-to-noise ratio and the target signal-to-noise ratio. The technical problem of high overhead of signal detection in the prior art is solved.

The invention provides an optimization design method for an inter-band cascade infrared detector, and the method comprises the following steps: S1, generating structural combinations through changing the area A of an absorption region of the inter-band cascade detector and the thickness dm of each stage of absorption region, and calculating the quantum efficiency QE of each structural combination; s2, enabling the influence of the interface mutual diffusion phenomenon of the inter-band cascade structure on carrier collection to be equivalent to a potential barrier, building a dark current calculation model of the mid-infrared inter-band cascade detector, and calculating the calculation dark current value of the inter-band cascade detector of each structure combination; s3, calculating a corresponding equivalent noise power NEP, and constructing a corresponding curve of the equivalent noise power NEP and a corresponding structure combination; and S4, according to the NEP values in the step S3, selecting the minimum NEP value, and determining the structure combination corresponding to the minimum NEP value as the structure with the optimal detector performance. According to the method, the calculation precision under the reverse bias voltage is improved, the temperature condition of the working environment is fully considered, and corresponding performance adjustment and optimization are carried out.

The invention relates to an LDPC (Low Density Parity Check) quantitative hierarchical decoding working method combining an improved dragonfly algorithm with residual degradation, and belongs to the technical field of wireless communication. The method specifically comprises the steps that firstly, a pilot signal is sent by a signal source, average least square estimation of channel state information is obtained through analysis based on representation of a received signal in a time domain and a frequency domain, noise power is determined, then the pilot signal is introduced into an improved dragonfly algorithm, quantization parameter set training is carried out, and the improved dragonfly algorithm reads a sample signal to obtain the channel state information. And finally, applying the self-adaptive quantization parameter set obtained by training to a residual degradation decoding algorithm, and if a decoding result does not meet a verification equation, carrying out next iteration. The performance of the residual degradation decoding algorithm is superior to that of the DLNMS, hardware resources are saved, the decoding performance of layered quantization is improved, the decoding time is shortened, and therefore the decoding speed is increased.

The invention provides a water quality suspended matter detection system and method based on sensing data, and belongs to the technical field of water quality suspended matter detection. Gain compensation is performed on a mixed optical signal based on backward spontaneous radiation noise power, so that the influence of self gain drift of a sensor and environmental interference on a signal baseline is effectively eliminated; the adaptive variational mode decomposition algorithm decomposes the standardized signal into a plurality of intrinsic mode functions, accurately extracts signals strongly related to the physical characteristics of the target suspended particulate matter, generates a particulate matter characteristic waveform signal with an optimized signal-to-noise ratio through the intrinsic mode functions screened out through weighted stacking, further highlights the time-frequency characteristics of the target signal, and improves the accuracy of the particulate matter characteristic waveform signal. Each independent particulate matter signal event is accurately separated by adopting a dynamic threshold peak value detection algorithm, and the detection accuracy is improved by extracting a multi-dimensional feature vector from each signal event and distinguishing target particulate matters from interferents by utilizing a pre-trained event classifier.